QI 106 Lesson 4: A Deeper Dive into Run Charts
When you analyze a run chart, you’re looking for non-random patterns in the data — that is, evidence that performance has actually changed as a result of your PDSA cycles. But how can you tell if the variation you’re seeing is random or non-random? In this lesson, you’ll practice using four rules to help you “read” a run chart and determine whether your changes have led to improvement.

Note: To make the most of this course, you’ll need Microsoft Word and Excel; versions 2010 or 2013 will work best. This course is not optimized for mobile devices.
Estimated Time of Completion: 30 minutes
Learning Objectives
After completing this lesson, you will be able to:
1. Identify non-random patterns in data.
2. Analyze data using a run chart.
3. Determine whether run charts show that your changes have led to improvement.
Kevin Little, Ph.D, Principal, Informing Ecological Design, LLC View Profile
Kathleen Vega, BA, Freelance Writer, Kathleen B. Vega, Inc View Profile
Matthew Eggebrecht, Senior Consultant, University of Minnesota View Profile
Lloyd Provost, MS, Statistician, Associates in Process Improvement View Profile
Richard Scoville, PhD, Improvement Advisor/Consultant, Institute for Healthcare Improvement View Profile
You must be a registered IHI.org user to take this lesson.
You must achieve a minimum score of 75% to successfully complete this lesson.